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A curriculum framework for embedding artificial intelligence literacies in pre-registration nursing education
Emily Tomlinson1, Monica Schoch1, Jo McDonall1
1School of Nursing and Midwifery & Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, 1 Gheringhap Street, Geelong, Vic., 3220, Australia.
Background:
Pre-registration nursing students need to be appropriately prepared for a healthcare environment that is increasingly utilising artificial intelligence. Currently, there are no guidelines available for embedding critical artificial intelligence literacies into nursing curricula.
Purpose:
This paper presents a novel curriculum framework that was developed for systematically embedding critical artificial intelligence literacy across a three-year pre-registration nursing program.
Framework Development:
The proposed framework was developed after the pilot implementation of artificial intelligence literacies into the pre-registration nursing program at Deakin University in Victoria, Australia. Consultation with university staff including academics and specialist learning designers was undertaken. The proposed framework aligns with professional clinical guidelines and the institutions artificial intelligence principles document.
Curriculum Framework:
This framework proposes scaffolded learning outcomes, example content and skills for use in each year of the program. In year one students can be introduced to foundational artificial intelligence concepts in academic contexts. In year two the content transitions to healthcare applications; and in year three there is an emphasis on practical clinical implementation. The proposed framework provides academics with clear learning outcomes, example content, and skill development goals specific to embedding artificial intelligence.
Conclusion:
The structured approach in this framework aims to ensure that nursing graduates develop critical skills in artificial intelligence evaluation, ethical understandings, and clinical application. Future directions include broader adoption across healthcare education programs and continuous framework refinement through collaborative co-design approaches.
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